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An expression signature of estrogen-regulated genes predicts disease-free survival in tamoxifen-treated patients better than progesterone receptor status.

ABSTRACT: We have used data derived from hormonal responses in human breast cancer cell lines to develop a panel of 36 genes which can robustly identify patients who will or will not benefit from tamoxifen treatment. These genes had the following characteristics: 1) induction by 17beta-estradiol (E2) in estrogen receptor (ER)-positive breast cancer cell lines in vitro, 2) under-expression in ER-negative breast tumors, and 3) correlation with PR mRNA expression in breast tumors. The average expression of these 36 genes was used as a "risk index" for assessing disease-specific survival in two independent tumor profile datasets of 60 and 67 patients treated with tamoxifen (these data not having been used to initially select the 36 genes), with a high risk group in each dataset defined as those with the bottom 25% of risk index values. This combined biological and informatic analysis is potentially applicable to many other cancer therapeutics.

SUBMITTER: Lippman ME

PROVIDER: S-EPMC2442700 | biostudies-literature | 2008

REPOSITORIES: biostudies-literature

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An expression signature of estrogen-regulated genes predicts disease-free survival in tamoxifen-treated patients better than progesterone receptor status.

Lippman Marc E ME Rae James M JM Chinnaiyan Arul M AM

Transactions of the American Clinical and Climatological Association 20080101

We have used data derived from hormonal responses in human breast cancer cell lines to develop a panel of 36 genes which can robustly identify patients who will or will not benefit from tamoxifen treatment. These genes had the following characteristics: 1) induction by 17beta-estradiol (E2) in estrogen receptor (ER)-positive breast cancer cell lines in vitro, 2) under-expression in ER-negative breast tumors, and 3) correlation with PR mRNA expression in breast tumors. The average expression of t ...[more]

PMID: 18596862

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Project description:PurposeRecent data have shown that the expression levels of long noncoding RNAs (lncRNAs) are associated with tamoxifen sensitivity in estrogen receptor (ER)-positive breast cancer. Herein, we constructed an lncRNA-based model to predict disease outcomes of ER-positive breast cancer patients treated with tamoxifen.MethodsLncRNA expression information was acquired from Gene Expression Omnibus by re-mapping pre-existing microarrays of patients with ER-positive breast cancer treated with tamoxifen. The distant metastasis-free survival (DMFS) predictive signature was subsequently built based on a Cox proportional hazard regression model in discover cohort patients, which was further evaluated in another independent validation dataset.ResultsSix lncRNAs were found to be associated with DMFS in the discover cohort, which were used to construct a tamoxifen efficacy-related lncRNA signature (TLS). There were 133 and 362 patients with TLS high- and low-risk signatures in the discover cohort. Both univariate and multivariate analysis demonstrated that TLS was associated with DMFS. TLS high-risk patients had worse outcomes than low-risk patients, with a hazard ratio of 4.04 (95% confidence interval, 2.83-5.77; p<0.001). Both subgroup analysis and receiver operating characteristic analysis indicated that TLS performed better in lymph node-negative, luminal B, 21-gene recurrence score high-risk, and 70-gene prognosis signature high-risk patients. Moreover, in a comparison of the 21-gene recurrence score and 70-gene prognosis signature, TLS showed a similar area under receiver operating characteristic curve in all patients. Gene Set Enrichment Analysis indicated that TLS high-risk patients showed different gene expression patterns related to the cell cycle and nucleotide metabolism from those of low-risk patients.ConclusionThis six-lncRNA signature was associated with disease outcome in ER-positive breast cancer patients treated with tamoxifen, which is comparable to previous messenger RNA signatures and requires further clinical evaluation.

Project description:BACKGROUND:Tamoxifen is considered a prodrug of its active metabolite endoxifen, which is dependent on the CYP2D6 and CYP3A enzymes. Tamoxifen pharmacokinetic variability influences endoxifen exposure and, consequently, its clinical outcome. This study investigated the impact of hormonal status on the pharmacokinetics of tamoxifen and its metabolites in TAM-treated breast cancer patients. METHODS:TAM-treated breast cancer patients (n?=?40) previously believed to have CYP3A activity within the normal range based on oral midazolam and phenotyped as CYP2D6 normal metabolizers using oral metoprolol were divided into two groups according to premenopausal (n?=?20; aged 35-50?years) or postmenopausal (n?=?20; aged 60-79?years) status. All patients were treated with 20?mg/day tamoxifen for at least three months. Serial plasma samples were collected within the 24?h dose interval for analysis of unchanged tamoxifen, endoxifen, 4-hydroxytamoxifen and N-desmethyltamoxifen quantified by LC-MS/MS. CYP activities were assessed using midazolam apparent clearance (CYP3A) and the metoprolol/alfa-hydroxymetoprolol plasma metabolic ratio (CYP2D6). CYP3A4, CYP3A5 and CYP2D6 SNPs and copy number variation were investigated using TaqMan assays. RESULTS:Postmenopausal status increased steady-state plasma concentrations (Css) of tamoxifen (116.95 vs 201.23?ng/mL), endoxifen (8.01 vs 18.87?ng/mL), N-desmethyltamoxifen (485.16 vs 843.88?ng/mL) and 4-hydroxytamoxifen (2.67 vs 4.11?ng/mL). The final regression models included hormonal status as the only predictor for Css of tamoxifen [?-coef ± SE, p-value (75.03?±?17.71, p?=?0.0001)] and 4-hydroxytamoxifen (1.7822?±?0.4385, p?=?0.0002), while endoxifen Css included hormonal status (8.578?±?3.402, p?=?0.02) and race (11.945?±?2.836, p?=?0.007). For N-desmethyltamoxifen Css, the final model was correlated with hormonal status (286.259?±?76.766, p?=?0.0007) and weight (-?8.585?±?3.060, p?=?0.008). CONCLUSION:The premenopausal status was associated with decreased endoxifen plasma concentrations by 135% compared to postmenopausal status. Thus, the endoxifen plasma concentrations should be monitored mainly in the premenopausal period to maintain plasma levels above the efficacy threshold value. TRIAL REGISTRATION:RBR-7tqc7k.

Project description:RNA modification of m6A/m5C/m1A contributes to the occurrence and development of cancer. Consequently, this study aimed to investigate the functions of m6A/m5C/m1A regulated genes in the prognosis and immune microenvironment of hepatocellular carcinoma (HCC). The expression levels of 45 m6A/m5C/m1A regulated genes in HCC tissues were determined. The functional mechanisms and protein-protein interaction network of m6A/m5C/m1A regulated genes were investigated. The Cancer Genome Atlas (TCGA) HCC gene set was categorized based on 45 m6A/m5C/m1A regulated genes, and survival analysis was used to determine the relationship between the overall survival of HCC patients in subgroups. Cox and least absolute shrinkage and selection operator (LASSO) regression analyses were used to construct the risk model and nomogram for m6A/m5C/m1A regulated genes. The relationships between m6A/m5C/m1A regulated gene subsets and risk model and immune cell infiltration were analyzed using CIBERSORT. m6A/m5C/m1A regulated genes were involved in mRNA and RNA modifications, mRNA and RNA methylation, mRNA and RNA stability, and other processes. There was a statistically significant difference between cluster1 and cluster2 groups of genes regulated by m6A/m5C/m1A. The prognosis of cluster1 patients was significantly better than that of cluster2 patients. There were statistically significant differences between the two cluster groups in terms of fustat status, grade, clinical stage, and T stage of HCC patients. The risk model comprised the overexpression of YBX1, ZC3H13, YTHDF1, TRMT10C, YTHDF2, RRP8, TRMT6, LRPPRC, and IGF2BP3, which contributed to the poor prognosis of HCC patients. The high-risk score was associated with prognosis, fustat status, grade, clinical stage, T stage, and M stage and was an independent risk factor for poor prognosis in HCC patients. High-risk score mechanisms included spliceosome, RNA degradation, and DNA replication, among others, and high-risk was closely related to stromal score, CD4 memory resting T cells, M0 macrophages, M1 macrophages, resting mast cells, CD4 memory activated T cells, and follicular helper T cells. In conclusion, the cluster subgroup and risk model of m6A/m5C/m1A regulated genes were associated with the poor prognosis and immune microenvironment in HCC and are expected to be the new tools for assessing the prognosis of HCC patients.

Dataset Information

An expression signature of estrogen-regulated genes predicts disease-free survival in tamoxifen-treated patients better than progesterone receptor status.

Publications

An expression signature of estrogen-regulated genes predicts disease-free survival in tamoxifen-treated patients better than progesterone receptor status.

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